Genomics

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9

Schmidt AF1,2,3, Holmes MV4, Preiss D4, Swerdlow DI5,6, Denaxas S7,8,9,10, Fatemifar G7,8,9, Faraway R5, Finan C5,7, Valentine D7,11, Fairhurst-Hunter Z12, Hartwig FP13, Horta BL13, Hypponen E14,15,16, Power C15, Moldovan M16, van Iperen E17,18, Hovingh K19, Demuth I20,21, Norman K22,23,24, Steinhagen-Thiessen E20, Demuth J25, Bertram L26,27, Lill CM28,29,30, Coassin S31, Willeit J32, Kiechl S32, Willeit K32,33, Mason D34, Wright J34, Morris R35, Wanamethee G35, Whincup P36, Ben-Shlomo Y37, McLachlan S38, Price JF38, Kivimaki M39, Welch C39, Sanchez-Galvez A39, Marques-Vidal P40, Nicolaides A41,42, Panayiotou AG43, Onland-Moret NC44, van der Schouw YT44, Matullo G45,46, Fiorito G45,46, Guarrera S45,46, Sacerdote C47, Wareham NJ48, Langenberg C48, Scott RA48, Luan J48, Bobak M39, Malyutina S49,50, Pająk A51, Kubinova R52, Tamosiunas A53, Pikhart H39, Grarup N54, Pedersen O54, Hansen T54, Linneberg A55,56, Jess T56, Cooper J57, Humphries SE57, Brilliant M58, Kitchner T58, Hakonarson H59, Carrell DS60, McCarty CA61, Lester KH62, Larson EB60, Crosslin DR63, de Andrade M64, Roden DM65, Denny JC66, Carty C67, Hancock S68, Attia J68,69, Holliday E68,69, Scott R68, Schofield P70, O'Donnell M71, Yusuf S71, Chong M71, Pare G71, van der Harst P17,18,72,73, Said MA73, Eppinga RN73, Verweij N73, Snieder H74; Lifelines Cohort authors, Christen T75, Mook-Kanamori DO75; ICBP Consortium, Gustafsson S76, Lind L77,78, Ingelsson E76,77, Pazoki R79,80, Franco O79, Hofman A79, Uitterlinden A79, Dehghan A79, Teumer A81,82, Baumeister S81,83, Dörr M82,84, Lerch MM85, Völker U82,86, Völzke H81,82, Ward J87, Pell JP87, Meade T88, Christophersen IE89, Maitland-van der Zee AH90,91, Baranova EV92, Young R92, Ford I92, Campbell A93, Padmanabhan S94, Bots ML43, Grobbee DE43, Froguel P95,96, Thuillier D95, Roussel R97,98,99, Bonnefond A95, Cariou B100, Smart M101, Bao Y102, Kumari M103, Mahajan A102, Hopewell JC12, Seshadri S103; METASTROKE Consortium of the ISGC, Dale C11, Costa RPE11, Ridker PM104, Chasman DI104, Reiner AP105, Ritchie MD106, Lange LA107, Cornish AJ108, Dobbins SE108, Hemminki K109,110, Kinnersley B108, Sanson M111,112, Labreche K111,112, Simon M113, Bondy M114, Law P108, Speedy H108, Allan J115, Li N108, Went M108, Weinhold N116, Morgan G116, Sonneveld P117, Nilsson B118, Goldschmidt H119, Sud A108, Engert A120, Hansson M121,122, Hemingway H7,8,9,123, Asselbergs FW5,124,7,125, Patel RS5,7,126, Keating BJ127, Sattar N94, Houlston R108, Casas JP128, Hingorani AD5,7.

 2019 Oct 29;19(1):240. doi: 10.1186/s12872-019-1187-z. PMID  31664920

2019

Author information

1
Institute of Cardiovascular Science, University College London, 222 Euston Road, London, NW1 2DA, UK. amand.schmidt@ucl.ac.uk.
2
Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. amand.schmidt@ucl.ac.uk.
3
UCL's BHF Research Accelerator Centre, London, UK. amand.schmidt@ucl.ac.uk.
4
Medical Research Council Population Health Research Unit, Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
5
Institute of Cardiovascular Science, University College London, 222 Euston Road, London, NW1 2DA, UK.
6
Department of Medicine, Imperial College London, London, UK.
7
UCL's BHF Research Accelerator Centre, London, UK.
8
Health Data Research UK, University College London, 222 Euston Road, London, NW1 2DA, UK.
9
Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK.
10
The Alan Turing Institute, British Library, 96 Euston Rd, London, NW1 2DB, UK.
11
University College London, Farr Institute of Health Informatics, London, UK.
12
Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK.
13
Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.
14
Centre for Population Health Research, Sansom Institute for Health Research, University of South Australia, Adelaide, Australia.
15
Population, Policy and Practice, UCL GOS Institute of Child Health, London, UK.
16
South Australian Health and Medical Research Institute, Adelaide, Australia.
17
Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, The Netherlands.
18
Department of Clinical Epidemiology, Biostatistics And Bioinformatics, Academic Medical Center Amsterdam, Amsterdam, the Netherlands.
19
Department of vascular medicine, Academic Medical Center Amsterdam, Amsterdam, the Netherlands.
20
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Berlin, Germany.
21
Charité - Universitätsmedizin Berlin, BCRT - Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany.
22
Institute of Nutritional Science, University of Potsdam, 14558, Nuthetal, Germany.
23
Geriatrics Research Group, Charité - Universitätsmedizin Berlin, 13347, Berlin, Germany.
24
Department of Nutrition and Gerontology, German Institute of Human Nutrition Potsdam-Rehbruecke, 14558, Nuthetal, Germany.
25
E.CA Economics GmbH, Berlin, Germany.
26
Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.
27
Center for Lifespan Changes in Brain and Cognition (LCBC), Dept. Psychology, University of Oslo, Oslo, Norway.
28
Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.
29
Institute of Human Genetics, Lübeck, Germany.
30
Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK.
31
Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, 6020, Innsbruck, Austria.
32
Department of Neurology, Medical University Innsbruck, Innsbruck, Austria.
33
Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
34
Bradford Institute for Health Research, Bradford Royal Infirmary, Bradford, UK.
35
Department Primary Care & Population Health, University College London, London, UK.
36
Population Health Research Institute, St George's, University of London, London, UK.
37
Population Health Sciences, University of Bristol, Bristol, UK.
38
Centre for Population Health Sciences, The Usher Institute, University of Edinburgh, Edinburgh, UK.
39
Department of Epidemiology and Public Health, UCL Institute of Epidemiology and Health Care, University College London, London, UK.
40
Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland.
41
Department of Vascular Surgery, Imperial College, London, United Kingdom.
42
Department of Surgery, Nicosia Medical School, University of Nicosia, Nicosia, Cyprus.
43
Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Limassol, Cyprus.
44
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
45
Italian Institute for Genomic Medicine (IIGM), Turin, Italy.
46
Department of Medical Sciences, University of Turin, Turin, Italy.
47
Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy.
48
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, UK.
49
Novosibirsk State Medical University, Novosibirsk, Russian Federation.
50
Institute of Internal and Preventive Medicine, Siberian Branch of the Russian Academy of Medical Sciences, Novosibirsk, Russian Federation.
51
Department of Epidemiology and Population Studies, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland.
52
National Institute of Public Health, Prague, Czech Republic.
53
Lithuanian University of Health Sciences, Kaunas, Lithuania.
54
Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
55
Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
56
Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, The Capital Region of Denmark, Denmark.
57
Centre for Cardiovascular Genetics, Department of Medicine, University College London, London, UK.
58
Center for Human Genetics, Marshfield Clinic Research Institute, Marshfield, USA.
59
Children's Hospital of Philadelphia, Philadelphia, USA.
60
Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
61
University of Minnesota, Minneapolis, USA.
62
Geisinger, Danville, USA.
63
Department of Biomedical Informatics and Medical Education University of Washington Seattle, Seattle, WA, USA.
64
Mayo Clinic, Rochester, USA.
65
Department of Medicine, Department of Pharmacology, Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA.
66
Vanderbilt University, Nashville, USA.
67
WHI, Seattle, USA.
68
University of Newcastle, Newcastle, NSW, Australia.
69
Public Health Program, Hunter Medical Research Institute, Newcastle, NSW, Australia.
70
Hunter New England Local Health District, Newcastle, NSW, Australia.
71
Population Health Research Institute, Hamilton, Ontario, Canada.
72
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
73
Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
74
Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
75
Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
76
Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden.
77
Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
78
Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
79
Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
80
Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
81
Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
82
DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
83
Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany.
84
Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany.
85
Department of Internal Medicine A, University Medicine Greifswald, Greifswald, Germany.
86
Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.
87
Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, Scotland, UK.
88
Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
89
The Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway.
90
Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute of Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands.
91
Department of Respiratory Medicine, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands.
92
Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK.
93
Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
94
Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.
95
CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, 59000, Lille, France.
96
Department of Genomics of Common Disease, Imperial College London, W12 0NN, London, United Kingdom.
97
INSERM, U-1138, Centre de Recherche des Cordeliers, Paris, France.
98
UFR de Médecine, Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
99
Départment de Diabétologie, Endocrinologie et Nutrition, Assistance Publique Hôpitaux de Paris, Hôpital Bicha, Paris, France.
100
l'institut du Thorax, INSERM, CNRS, UNIV Nantes, CHU Nantes, Nantes, France.
101
Institute for Social and Economic Research, University of Essex, Essex, UK.
102
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, England.
103
Boston University School of Medicine, Boston, MA, USA.
104
Harvard Medical School Center for Cardiovascular Disease Prevention Brigham and Women's Hospital, Boston, USA.
105
UWash, Seattle, USA.
106
Penn State, State College, USA.
107
University of Colorado Denver, Denver, USA.
108
Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
109
Div. Molecular Genetic Epidemiology German Cancer Research Center, Im Neuenheimer Feld 580, 69120, Heidelberg, Germany.
110
Deutsches Krebsforschungszentrum, Heidelberg, Germany.
111
The Institut du Cerveau et de la Moelle épinière - ICM, Paris, France.
112
Sorbonne Universités, UPMC Université Paris 06, UMR S 1127, F-75013, Paris, France.
113
Department of Neurosurgery, Bethel Clinic, Kantensiek 11, 33617, Bielefeld, Germany.
114
Division of Hematology-Oncology, Department of Pediatrics, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, 77030, USA.
115
Northern Institute for Cancer Research, Newcastle University, Newcastle upon Tyne, UK.
116
Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, USA.
117
Department of Hematology, Erasmus MC Cancer Institute, 3075 EA, Rotterdam, the Netherlands.
118
Hematology and Transfusion Medicine, Department of Laboratory Medicine, BMC B13, SE-221 84, Lund, Sweden.
119
University Clinic Heidelberg, Internal Medicine V and National Center for Tumor Diseases (NCT), Heidelberg, Germany.
120
Department of Internal Medicine, University Hospital of Cologne, Cologne, Germany.
121
Hematology Clinic, Skåne University Hospital, Skåne, Sweden.
122
Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
123
The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, NW1 2DA, UK.
124
Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
125
Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom.
126
The Barts Heart Centre, St Bartholomew's Hospital, London, UK.
127
UPenn, Philadelphia, USA.
128
Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC) Veterans Affairs Boston Healthcare System, Boston, USA.

 

Abstract

Background: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9.

Methods: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration.

Results: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable.

Conclusions: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

 

A bird's-eye view of Italian genomic variation through whole-genome sequencing

Cocca M1, Barbieri C2, Concas MP1, Robino A1, Brumat M3, Gandin I3, Trudu M4, Sala CF2, Vuckovic D5, Girotto G1,3, Matullo G6,7, Polasek O8, Kolčić I8, Gasparini P1,3, Soranzo N5, Toniolo D2, Mezzavilla M9.

2019 Nov 29. doi: 10.1038/s41431-019-0551-x. [Epub ahead of print] PMID: 31784700

2019

Author information

  1. Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy.
  2. Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy.
  3. Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy.
  4. Molecular Genetics of Renal Disorders Unit, Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy.
  5. Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK.
  6. Department of Medical Sciences, University of Turin, Turin, Italy.
  7. Italian Institute for Genomic Medicine (IIGM), Turin, Italy.
  8. Public Health, University of Split, Split, Croatia.
  9. Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy. massimo.mezzavilla@burlo.trieste.it.

 

Abstract

The genomic variation of the Italian peninsula populations is currently under characterised: the only Italian whole-genome reference is represented by the Tuscans from the 1000 Genome Project. To address this issue, we sequenced a total of 947 Italian samples from three different geographical areas. First, we defined a new Italian Genome Reference Panel (IGRP1.0) for imputation, which improved imputation accuracy, especially for rare variants, and we tested it by GWAS analysis on red blood traits. Furthermore, we extended the catalogue of genetic variation investigating the level of population structure, the pattern of natural selection, the distribution of deleterious variants and occurrence of human knockouts (HKOs). Overall the results demonstrate a high level of genomic differentiation between cohorts, different signatures of natural selection and a distinctive distribution of deleterious variants and HKOs, confirming the necessity of distinct genome references for the Italian population.

 

Ancient Rome: A genetic crossroads of Europe and the Mediterranean

Antonio ML#1, Gao Z#2,3, Moots HM#4, Lucci M5, Candilio F6,7, Sawyer S8, Oberreiter V8, Calderon D1, Devitofranceschi K8, Aikens RC1, Aneli S9, Bartoli F10, Bedini A11, Cheronet O8, Cotter DJ3, Fernandes DM8,12, Gasperetti G13, Grifoni R14, Guidi A15, La Pastina F7, Loreti E16, Manacorda D17, Matullo G9, Morretta S18, Nava A5,19, Fiocchi Nicolai V20, Nomi F15, Pavolini C21, Pentiricci M16, Pergola P22, Piranomonte M23, Schmidt R24, Spinola G25, Sperduti A19,26, Rubini M27,28, Bondioli L19, Coppa A29, Pinhasi R#30, Pritchard JK#31,3,28.

Science. 2019 Nov 8;366(6466):708-714. doi: 10.1126/science.aay6826. PMID: 31699931

 

2019

Author information

1
Program in Biomedical Informatics, Stanford University, Stanford, CA, USA.
2
Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
3
Department of Genetics, Stanford University, Stanford, CA, USA.
4
Stanford University, Department of Anthropology, Stanford, CA, USA.
5
DANTE Laboratory for the study of Diet and Ancient Technology, Sapienza Università di Roma, Rome, Italy.
6
School of Archaeology, University College Dublin, Dublin, Ireland.
7
Dipartimento di Biologia Ambientale, Sapienza Università di Roma, Rome, Italy.
8
Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria.
9
Dipartimento di Scienze Mediche, Università di Torino, Torino, Italy.
10
Dipartimento di Biologia, Università di Pisa, Pisa, Italy.
11
Ministero dei Beni e delle Attività Culturali (retired), Rome, Italy.
12
CIAS, Department of Life Sciences, University of Coimbra, Coimbra, Portugal.
13
Soprintendenza Archeologia, belle arti e paesaggio per le province di Sassari e Nuoro, Sassari, Italy.
14
Dipartimento di Civiltà e Forme del Sapere, Università di Pisa, Pisa, Italy.
15
Dipartimento di Studi Umanistici, Università degli Studi di Roma Tre, Rome, Italy.
16
Curatore beni culturali presso la Sovrintendenza Capitolina, Rome, Italy.
17
Dipartimento di Studi Umanistici Università degli Studi di Roma Tre, Rome, Italy.
18
Soprintendenza Speciale Archeologia Belle Arti e Paesaggio di Roma, Rome, Italy.
19
Servizio di Bioarcheologia, Museo delle Civiltà, Rome, Italy.
20
Christian and Medieval Archaeology, University of Rome Tor Vergata, Rome, Italy.
21
Università della Tuscia, DISUCOM Dipartimento di Scienze Umanistiche, della Comunicazione e del Turismo, Viterbo, Italy.
22
Aix-Marseille University, Marseille, France.
23
Soprintendenza speciale Archeologia Belle arti e paesaggio di Roma, Rome, Italy.
24
University College Dublin, Dublin, Ireland.
25
Musei Vaticani, Reparto Antichità Greche e Romane, Vatican City.
26
Dipartimento di Archeologia, Università di Foggia, Foggia, Italy.
27
SABAP-LAZ Ministero dei Beni e delle Attività Culturali, Rome, Italy.
28
Department of Biology, Stanford University, Stanford, CA, USA.
29
Dipartimento di Biologia Ambientale, Sapienza Università di Roma, Rome, Italy. pritch@stanford.edu ron.pinhasi@univie.ac.at alfredo.coppa@uniroma1.it.
30
Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria. pritch@stanford.edu ron.pinhasi@univie.ac.at alfredo.coppa@uniroma1.it.
31
Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA. pritch@stanford.edu ron.pinhasi@univie.ac.at alfredo.coppa@uniroma1.it.
#
Contributed equally

 

Abstract

Ancient Rome was the capital of an empire of ~70 million inhabitants, but little is known about the genetics of ancient Romans. Here we present 127 genomes from 29 archaeological sites in and around Rome, spanning the past 12,000 years. We observe two major prehistoric ancestry transitions: one with the introduction of farming and another prior to the Iron Age. By the founding of Rome, the genetic composition of the region approximated that of modern Mediterranean populations. During the Imperial period, Rome's population received net immigration from the Near East, followed by an increase in genetic contributions from Europe. These ancestry shifts mirrored the geopolitical affiliations of Rome and were accompanied by marked interindividual diversity, reflecting gene flow from across the Mediterranean, Europe, and North Africa.

 

Improving the prediction of cardiovascular risk with machine-learning and DNA methylation data

Giovanni Cugliari, Silvia Benevenuta, Simonetta Guarrera, Carlotta Sacerdote, Salvatore Panico, Vittorio Krogh, Rosario Tumino, Paolo Vineis, Piero Fariselli, Giuseppe Matullo

CIBCB Siena 2019

Prognostic value of blood DNA methylation in Malignant Pleural Mesothelioma

 

Giovanni Cugliari, Simonetta Guarrera,Clara Viberti, Federica Grosso, Elisabetta Casalone, Marta Betti , Daniela Ferrante, Anna Aspesi, Caterina Casadio, Roberta Libener, Ezio Piccolini, Dario Mirabelli, Corrado Magnani, Irma Dianzani, Giuseppe Matullo

SIGU Catania 2018

Advances in the Genetics of Hypertension: The Effect of Rare Variants

Russo A1,2, Di Gaetano C3,4, Cugliari G5,6, Matullo G7,8.

 2018 Feb 28;19(3). pii: E688. doi: 10.3390/ijms19030688. PMID:  29495593

 
2018

Author information

1
Department of Medical Sciences, University of Turin, 10126 Turin, Italy. alessia.russo@hugef.org.
2
Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy. alessia.russo@hugef.org.
3
Department of Medical Sciences, University of Turin, 10126 Turin, Italy. cornelia.digaetano@unito.it.
4
Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy. cornelia.digaetano@unito.it.
5
Department of Medical Sciences, University of Turin, 10126 Turin, Italy. giovanni.cugliari@hugef.org.
6
Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy. giovanni.cugliari@hugef.org.
7
Department of Medical Sciences, University of Turin, 10126 Turin, Italy. giuseppe.matullo@unito.it.
8
Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy. giuseppe.matullo@unito.it.

 

Abstract

Worldwide, hypertension still represents a serious health burden with nine million people dying as a consequence of hypertension-related complications. Essential hypertension is a complex trait supported by multifactorial genetic inheritance together with environmental factors. The heritability of blood pressure (BP) is estimated to be 30-50%. A great effort was made to find genetic variants affecting BP levels through Genome-Wide Association Studies (GWAS). This approach relies on the "common disease-common variant" hypothesis and led to the identification of multiple genetic variants which explain, in aggregate, only 2-3% of the genetic variance of hypertension. Part of the missing genetic information could be caused by variants too rare to be detected by GWAS. The use of exome chips and Next-Generation Sequencing facilitated the discovery of causative variants. Here, we report the advances in the detection of novel rare variants, genes, and/or pathways through the most promising approaches, and the recent statistical tests that have emerged to handle rare variants. We also discuss the need to further support rare novel variants with replication studies within larger consortia and with deeper functional studies to better understand how new genes might improve patient care and the stratification of the response to antihypertensive treatments.

 

Peripheral blood DNA methylation as potential biomarker of Malignant Pleural Mesothelioma in asbestos-exposed subjects. 

Guarrera S1, Viberti C1, Cugliari G1, Allione A1, Casalone E1, Betti M2, Ferrante D3, Aspesi A2, Casadio C4, Grosso F5, Libener R6, Piccolini E7, Mirabelli D8, Dianzani I9, Magnani C10, Matullo G11

 2019 Mar;14(3):527-539. doi: 10.1016/j.jtho.2018.10.163. Epub 2018 Nov 5. PMID: 30408567

2019

Author information

1
Italian Institute for Genomic Medicine, IIGM, Turin, Italy; Department of Medical Sciences, University of Turin, Turin, Italy.
2
Department of Health Sciences, University of Piemonte Orientale, Novara, Italy.
3
Medical Statistics and Cancer Epidemiology Unit, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy; Cancer Epidemiology Unit, CPO-Piemonte, Novara, Italy.
4
Thoracic Surgery Unit, AOU Maggiore Della Carità, Novara, Italy.
5
Division of Medical Oncology, SS. Antonio e Biagio General Hospital, Alessandria, Italy.
6
Pathology Unit, SS. Antonio e Biagio General Hospital, Alessandria, Italy.
7
Pneumology Unit, Santo Spirito Hospital, Casale Monferrato (AL), Italy.
8
Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy; Cancer Epidemiology Unit, CPO Piemonte, Turin, Italy; Interdepartmental Center for Studies on Asbestos and Other Toxic Particulates "G. Scansetti," University of Turin, Turin, Italy.
9
Department of Health Sciences, University of Piemonte Orientale, Novara, Italy; Interdepartmental Center for Studies on Asbestos and Other Toxic Particulates "G. Scansetti," University of Turin, Turin, Italy.
10
Medical Statistics and Cancer Epidemiology Unit, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy; Cancer Epidemiology Unit, CPO-Piemonte, Novara, Italy; Interdepartmental Center for Studies on Asbestos and Other Toxic Particulates "G. Scansetti," University of Turin, Turin, Italy.
11
Italian Institute for Genomic Medicine, IIGM, Turin, Italy; Department of Medical Sciences, University of Turin, Turin, Italy; Interdepartmental Center for Studies on Asbestos and Other Toxic Particulates "G. Scansetti," University of Turin, Turin, Italy; Medical Genetics Unit, AOU Città della Salute e della Scienza, Turin, Italy. Electronic address: giuseppe.matullo@unito.it.

 

Abstract

Introduction: Malignant pleural mesothelioma (MPM) is an aggressive tumor strongly associated with asbestos exposure. Patients are usually diagnosed when current treatments have limited benefits, highlighting the need for noninvasive early diagnostic tests to monitor asbestos-exposed people.

Methods: We used a genome-wide methylation array to identify, in asbestos-exposed subjects, novel blood DNA methylation markers of MPM in 163 MPM cases and 137 cancer-free controls (82 MPM cases and 68 controls, training set; replication in 81 MPM cases and 69 controls, test set) sampled from the same areas.

Results: Evidence of differential methylation between MPM cases and controls was found (more than 800 cytosine-guanine dinucleotide sites, false discovery rate p value (pfdr) < 0.05), mainly in immune system-related genes. Considering the top differentially methylated signals, seven single- cytosine-guanine dinucleotides and five genomic regions of coordinated methylation replicated with similar effect size in the test set (pfdr < 0.05). The top hypomethylated single-CpG (cases versus controls effect size less than -0.15, pfdr < 0.05 in both the training and test sets) was detected in FOXK1 (Forkhead-box K1) gene, an interactor of BAP1 which was found mutated in MPM tissue and as germline mutation in familial MPM. In the test set, comparison of receiver operating characteristic curves and the area under the curve (AUC) of two models, including or excluding methylation, showed a significant increase in case/control discrimination when considering DNA methylation together with asbestos exposure (AUC = 0.81 versus AUC = 0.89, DeLong's test p = 0.0013).

Conclusions: We identified signatures of differential methylation in DNA from whole blood between asbestos exposed MPM cases and controls. Our results provide the rationale to further investigate, in prospective studies, the potential use of blood DNA methylation profiles for the identification of early changes related to the MPM carcinogenic process.

 

Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults

Parmar P1, Lowry E1, Cugliari G2, Suderman M3, Wilson R4, Karhunen V5, Andrew T6, Wiklund P7, Wielscher M5, Guarrera S2, Teumer A8, Lehne B5, Milani L9, de Klein N10, Mishra PP11, Melton PE12, Mandaviya PR13, Kasela S14, Nano J15, Zhang W16, Zhang Y17, Uitterlinden AG18, Peters A19, Schöttker B20, Gieger C19, Anderson D21, Boomsma DI22, Grabe HJ23, Panico S24, Veldink JH25, van Meurs JBJ13, van den Berg L25, Beilin LJ26, Franke L10, Loh M27, van Greevenbroek MMJ28, Nauck M29, Kähönen M30, Hurme MA31, Raitakari OT32, Franco OH33, Slagboom PE34, van der Harst P35, Kunze S4, Felix SB36, Zhang T37, Chen W38, Mori TA26, Bonnefond A39, Heijmans BT34; BIOS Consortium, Muka T33, Kooner JS40, Fischer K14, Waldenberger M19, Froguel P39, Huang RC21, Lehtimäki T11, Rathmann W41, Relton CL3, Matullo G2, Brenner H20, Verweij N42, Li S43, Chambers JC44, Järvelin MR45, Sebert S46; GLOBAL Meth QTL Consortium.

 2018 Dec;38:206-216. doi: 10.1016/j.ebiom.2018.10.066. Epub 2018 Nov 13.  PMID 30442561

 
2018

Author information

1
Center for Life Course Health Research, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland.
2
Department of Medical Sciences, University of Turin, Turin, Italy; Italian Institute for Genomic Medicine, IIGM, Turin, Italy.
3
MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, UK.
4
Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Bavaria, Germany; Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology, Neuherberg, Bavaria, Germany.
5
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London.
6
Genomics of Common Disease, Department of Medicine, Imperial College London, London, UK.
7
Center for Life Course Health Research, University of Oulu, Oulu, Finland; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Department of Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
8
Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; Partner Site Greifswald, DZHK (German Centre for Cardiovascular Research), Greifswald, Germany.
9
Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Sweden.
10
Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands.
11
Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Centre - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
12
School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Australia; Curtin UWA Centre for Genetic Origins of Health and Disease, School of Biomedical Sciences, The University of Western Australia, Crawley, Australia.
13
Department of Internal Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands.
14
Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
15
Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology, Neuherberg, Bavaria, Germany; Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands.
16
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Department of Cardiology, Ealing Hospital, North West Healthcare NHS Trust, London, UK.
17
Division of Clinical Epidemiology and Aging Research, German Cancer Research Centre (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany.
18
Department of Internal Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands.
19
Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Bavaria, Germany; Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology, Neuherberg, Bavaria, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
20
Division of Clinical Epidemiology and Aging Research, German Cancer Research Centre (DKFZ), Im Neuenheimer Feld, Heidelberg, Germany; Network Aging Research, University of Heidelberg, Bergheimer Straße, Heidelberg, Germany.
21
Telethon Kids Institute, University of Western Australia, Perth, Australia.
22
Department of Biological Psychology, School of Public Health, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
23
Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; German Centre for Neurodegenerative Diseases DZNE, Site Rostock/Greifswald, Greifswald, Germany.
24
Department of Clinical Medicine and Surgery, Federico II University, Naples, Italy.
25
Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands.
26
Medical School, University of Western Australia, Perth, Australia.
27
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Immunos, Level 5, Singapore, Singapore; Institute of Health Sciences, University of Oulu, Finland.
28
Department of Internal Medicine and School for Cardiovascular Diseases (CARIM), Maastricht University Medical Centre, Maastricht, The Netherlands.
29
Partner Site Greifswald, DZHK (German Centre for Cardiovascular Research), Greifswald, Germany; Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
30
Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Centre - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
31
Department of Microbiology and Immunology, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
32
Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
33
Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, The Netherlands.
34
Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, The Netherlands.
35
Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands; Department of Cardiology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands; Durrer Centre for Cardiogenetic Research, ICIN - Netherlands Heart Institute, Utrecht, The Netherlands.
36
Partner Site Greifswald, DZHK (German Centre for Cardiovascular Research), Greifswald, Germany.
37
Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, USA; Department of Biostatistics, School of Public Health, Shandong University, Jinan, China.
38
Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, USA.
39
Genomics of Common Disease, Department of Medicine, Imperial College London, London, UK; European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, CNRS UMR 8199, Lille, France.
40
Department of Cardiology, Ealing Hospital, North West Healthcare NHS Trust, London, UK; Imperial College Healthcare NHS Trust, London, UK; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Imperial College London, National Heart and Lung Institute, London, UK.
41
Institute for Biometrics and Epidemiology, German Diabetes Centre, Leibniz Centre for Diabetes Research at Heinrich, Heine University, Düsseldorf, Germany.
42
Department of Cardiology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands.
43
Children's Hospitals and Clinics of Minnesota, Children's Minnesota Research Institute, Minneapolis, MN 55404, USA.
44
Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Department of Cardiology, Ealing Hospital, North West Healthcare NHS Trust, London, UK; Imperial College Healthcare NHS Trust, London, UK; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
45
Center for Life Course Health Research, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK. Electronic address: m.jarvelin@imperial.ac.uk.
46
Center for Life Course Health Research, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Medical Research Centre (MRC) Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland. Electronic address: sylvain.sebert@oulu.fi.

 

Abstract

Background: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health.

Methods: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n = 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP).

Findings: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0·012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 × 10-7 < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 × 10-8 < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels.

Interpretation: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. FUND: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH.

 

Population structure of modern-day Italians reveals patterns of ancient and archaic ancestries in Southern Europe

Raveane A1,2, Aneli S2,3,4, Montinaro F2,5, Athanasiadis G6, Barlera S7, Birolo G3,4, Boncoraglio G8,9, Di Blasio AM10, Di Gaetano C3,4, Pagani L5,11, Parolo S12, Paschou P13, Piazza A3,14, Stamatoyannopoulos G15, Angius A16, Brucato N17, Cucca F16, Hellenthal G18, Mulas A19, Peyret-Guzzon M20, Zoledziewska M16, Baali A21, Bycroft C20, Cherkaoui M21, Chiaroni J22,23, Di Cristofaro J22,23, Dina C24, Dugoujon JM17, Galan P25, Giemza J24, Kivisild T5,26, Mazieres S22, Melhaoui M27, Metspalu M5, Myers S20, Pereira L28,29, Ricaut FX17, Brisighelli F30, Cardinali I31, Grugni V1, Lancioni H31, Pascali VL30, Torroni A1, Semino O1, Matullo G3,4, Achilli A1, Olivieri A1, Capelli C2.

 2019 Sep 4;5(9):eaaw3492. doi: 10.1126/sciadv.aaw3492. eCollection 2019 Sep. PMID:31517044

 
2019

Author information

1
Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy.
2
Department of Zoology, University of Oxford, Oxford, UK.
3
Department of Medical Sciences, University of Turin, Turin, Italy.
4
IIGM (Italian Institute for Genomic Medicine), Turin, Italy.
5
Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia.
6
Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
7
Department of Cardiovascular Research, Istituto di Ricovero e Cura a Carattere Scientifico-Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy.
8
Department of Cerebrovascular Diseases, IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
9
PhD Program in Neuroscience, University Milano-Bicocca, Monza, Italy.
10
Istituto Auxologico Italiano, IRCCS, Centro di Ricerche e Tecnologie Biomediche, Milano, Italy.
11
APE lab, Department of Biology, University of Padua, Padua, Italy.
12
Computational Biology Unit, Institute of Molecular Genetics, National Research Council, Pavia, Italy.
13
Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
14
Academy of Sciences, Turin, Italy.
15
Department of Medicine and Genome Sciences, University of Washington, Seattle, WA, USA.
16
Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.
17
Evolutionary Medicine Group, Laboratoire d'Anthropologie Moléculaire et Imagerie de Synthèse, Centre National de la Recherche Scientifique (CNRS), Université de Toulouse, Toulouse, France.
18
University College London Genetics Institute (UGI), University College London, London, UK.
19
Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Lanusei, Italy.
20
The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
21
Faculté des Sciences Semlalia de Marrakech (FSSM), Université Cadi Ayyad, Marrakech, Morocco.
22
Aix Marseille Univ, CNRS, EFS, ADES, Marseille, France.
23
Etablissement Français du Sang PACA Corse, Biologie des Groupes Sanguins, Marseille, France.
24
l'institut du thorax, INSERM, CNRS, University of Nantes, Nantes, France.
25
Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre de Recherche en Epidémiologie et Statistiques, Université Paris 13/Inserm U1153/Inra U1125/ Cnam, COMUE Sorbonne Paris Cité, F-93017 Bobigny, France.
26
Department of Human Genetics, KU Leuven, Herestraat 49, box 604, Leuven 3000, Belgium.
27
Faculté des Sciences, Université Mohammed Premier, Oujda, Morocco.
28
i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.
29
IPATIMUP-Instituto de Patologia e Imunologia Molecular, Universidade do Porto, Porto, Portugal.
30
Section of Legal Medicine, Institute of Public Health, Catholic University of the Sacred Heart, Rome, Italy.
31
Department of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy.

 

Abstract

European populations display low genetic differentiation as the result of long-term blending of their ancient founding ancestries. However, it is unclear how the combination of ancient ancestries related to early foragers, Neolithic farmers, and Bronze Age nomadic pastoralists can explain the distribution of genetic variation across Europe. Populations in natural crossroads like the Italian peninsula are expected to recapitulate the continental diversity, but have been systematically understudied. Here, we characterize the ancestry profiles of Italian populations using a genome-wide dataset representative of modern and ancient samples from across Italy, Europe, and the rest of the world. Italian genomes capture several ancient signatures, including a non-steppe contribution derived ultimately from the Caucasus. Differences in ancestry composition, as the result of migration and admixture, have generated in Italy the largest degree of population structure detected so far in the continent, as well as shaping the amount of Neanderthal DNA in modern-day populations.

 

Germline mutations and new copy number variants among 40 pediatric cancer patients suspected for genetic predisposition

Gambale A, Russo R, Andolfo I, Quaglietta L, De Rosa G, Contestabile V, De Martino L, Genesio R, Pignataro P, Giglio S, Capasso M, Parasole R, Pasini B, Iolascon A.

Clin Genet. 2019 Oct;96(4):359-365. doi: 10.1111/cge.13600. Epub 2019 Jul 15. PMID 31278746

 

2019

Author information

1
Dipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Naples, Italy.
2
CEINGE Biotecnologie Avanzate, Naples, Italy.
3
Azienda Ospedaliera di Rilievo Nazionale Santobono Pausilipon, S.C. Pediatria Oncologia, Dip. di Oncoematologia Pediatrica Napoli, Italy.
4
Biomedical Experimental and Clinical Sciences "Mario Serio", University of Florence, Florence, Italy.
5
SOD Genetica Medica, Azienda Ospedaliero-Universitaria Meyer, Florence, Italy.
6
IRCCS SDN, Naples, Italy.
7
Dipartimento di Scienze Mediche, Università degli Studi di Torino, Torino, Italy.

 

Abstract

Cancer predisposition syndromes (CPS) result from germline pathogenic variants, and they are increasingly recognized in the etiology of many pediatric cancers. Herein, we report the genetic/genomic analysis of 40 pediatric patients enrolled from 2016 to 2018. Our diagnostic workflow was successful in 50% of screened cases. Overall, the proportion of CPS in our case series is 10.9% (20/184) of enrolled patients. Interestingly, 12.5% of patients achieved a conclusive diagnosis through the analysis of chromosomal imbalance. Indeed, we observed germline microdeletions/duplications of regions encompassing cancer-related genes in 50% of patients undergoing array-CGH: EIF3H duplication in a patient with infantile desmoplastic astrocytoma and low-grade Glioma; SLFN11 deletion, SOX4 duplication, and PARK2 partial deletion in three neuroblastoma patients; a PTPRD partial deletion in a child diagnosed with glioblastoma multiforme. Finally, we identified two cases due to DICER1 germline mutations.

 

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